Abstract: A method including obtaining image data and attribute information of a first item in an item catalog. The method also can include generating candidate variant items from the item catalog for the first item using a combination of (a) a k-nearest neighbors approach to search for first candidate variant items based on text embeddings for the attribute information of the first item, and (b) an elastic search approach to search for second candidate variant items based on image embeddings for the image data of the first item. The method additionally can include performing respective classifications based on respective pairs comprising the first item and each of the candidate variant items to filter the candidate variant items. The method further can include determining a respective distance between the first item and each of the candidate variant items, as filtered.

Abstract: A method, system and computer-readable storage medium for transferring data segments from one computer system to a second computing system. Prior to transfer of the data segments, the first system calculates compressibility ratio of each segment and compares the compressibility ratio to a preset threshold. Based on the comparison, the first system assigns a compressibility hint to each segment. The first system transfers the segments to the second system, together with the corresponding compressibility hint. The second system stores each segment in a compressible region or in a non-compressible region based on the hint. Then the second system compresses the compressible region and stores the compressed region in a container, and stores the non-compressible region uncompressed in the container.

Abstract: The present invention relates to a system and a method for updating data models. Input data received from a data source and/or prediction data obtained from a data model is reduced based on baseline reference data to obtain a plurality of representative points. The plurality of representative points are clustered to generate a plurality of clusters. An outlier cluster is detected from the plurality of clusters based on a maximum distance of the plurality of clusters from a highest density cluster and/or comparison of quantity and values of the plurality of representative points with predefined rules. Data drift is identified based on changes in densities of the plurality of clusters. The data model is updated using information corresponding to the outlier cluster and the data drift.

Abstract: Index management for non-relational database systems may be automatically performed. Performance of queries to a non-relational database may be evaluated to determine whether to create or remove an additional index. An additional index may be automatically created to store a subset of data projected from the non-relational database to utilize when performing a query to the non-relational database instead of accessing data in the non-relational database.

Abstract: The disclosure includes methods and systems that perform operations of identifying a behavior of a metric, where the metric is associated with a node of included within a nodal graph displayed on a graphical user interface. Additionally, a root cause of the behavior is determined through automated, computerized analytics, which may include execution of a search query associated with the node, and a notification of the root cause may be provided via the graphical user interface. Additionally, the graphical user interface may be configured to receive user input that results in the generation of a nodal graph, where the user input includes placement of nodes on a display screen and edges representing a connection between two nodes, where the edges may represent a dependency between the nodes.

Abstract: Example techniques are provided for the task of differentially private clustering. For several basic clustering problems, including Euclidean DensestBall, 1-Cluster, k-means, and k-median, the present disclosure provides efficient differentially private algorithms that achieve essentially the same approximation ratios as those that can be obtained by any non-private algorithm, while incurring only small additive errors. This improves upon existing efficient algorithms that only achieve some large constant approximation factors.

Abstract: A technique for generating and presenting context-aware recommendations to assist a patient in managing a chronic health condition. A health management platform provides various services that are accessible to a patient via a graphical user interface (GUI). Input data are received from various services and processed to generate contextual data associated with the patient such as a health state of the patient. Using the contextual data, a recommendation to access a particular service is generated and presented to the patient via the GUI. For example, in response to determining a health state of a patient, a recommendation to access a service to improve the health state of the patient can be automatically presented via the GUI to encourage the patient to access the service.

Abstract: Methods for data visibility in nested transactions in distributed systems are performed by systems and devices. Distributed executions of queries are performed in processing systems according to isolation level protocols with unique nested transaction identifiers for data management and versioning across one or more data sets, one or more compute pools, etc., within a logical server via a single transaction manager that oversees the isolation semantics and data versioning. A distributed query processor of the systems and devices performs nested transaction versioning for distributed tasks by generating nested transaction identifiers, encoded in data rows, which are used to enforce correct data visibility. Data visibility is restricted to previously committed data from distributed transactions and tasks, and is blocked for distributed transactions and tasks that run concurrently.

Abstract: Systems and methods for low latency materialized information provision are disclosed. For example, a system may include at least one memory storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, via a materialization service, data from multiple sources related to an item associated with a webpage hosted by a server. The data may include first event data sourced from a real-time feed and second event data sourced from stored data. Operations may include generating synchronized data based on the first and second event data. Operations may include receiving a request from the web server for information related to the item, the request being associated with a user segment. Operations may include identifying data to aggregate to fulfill the request, generating a data structure gathering synchronized data using the data structure, and forwarding the gathered synchronized data to the server.

Abstract: A first data management system, which may be associated with a content management system (CMS), may receive an identifier for a content item. A content item may be an example of a picture, a blog post, an article, a video, an audio segment (e.g., a podcast) or other type of text or multimedia content. The first data management system may be configured to generate an object corresponding to the content item. The content object may be transmitted to a model corresponding to a second data management system. The model may be configured to identify relationships between data stored at the second data management system. The model may identify one or more data objects that are associated with the received content object, and return the data objects to the first data management system.

Abstract: The method includes obtaining, by a restoration policy manager, a restoration request for a plurality of application containers, and in response to the restoration request: obtaining, by a backup server, container information associated with the plurality of application containers, assigning a restoration type to each application container in the plurality of application containers, updating a restoration type list based on the assigning, and initiating a restoration of the plurality of application containers using the restoration type list.

Abstract: A server can receive a seed keyword to generate additional keywords relevant to the seed keyword. The server can identify, using a semantic relationship graph, keyword categories. Each keyword can have a semantic distance from the seed keyword less than a threshold. The server can generate, for each keyword of the keyword categories, a keyword-seed affinity score based on a frequency of the keyword occurring with the seed keyword on an information resource. The server can determine, for each keyword category, a category-seed affinity score based on the keyword-seed affinity scores for each of keyword in the keyword category. The server can compare each category-seed affinity score a threshold. The server can transmit, for display, the keywords. One keyword category can be indicated as selected and another keyword category can be indicated as unselected based on the comparison.

Abstract: A system architecture for linking one or more derived objects to existing data objects in a data structure can be organized in a variety of forms. A method for establishing the architecture may include linking first and second data objects. linking first and second data objects. The first and second data objects may be associated with corresponding first and second pluralities of properties. The method may include receiving a first user limitation associated with at least one of the first or second pluralities of properties and receiving a second user limitation associated with at least one of the first or second pluralities of properties. The method can include deriving a conclusion object comprising a third plurality of properties comprising a subset of one or more of the first or second pluralities of properties and linking the conclusion object to the first and second data objects.

Abstract: In an approach to containerizing an existing database that currently resides on a standard operating system, responsive to determining that a non-containerized database is suitable for containerization, one or more database objects to be shifted into a container are determined. The one or more database objects are mapped to a container structure. The non-containerized database is shifted into the container based on the mapping of the one or more database objects and the container structure to create a containerized database.

Abstract: Discovering second-order documents and latent custodians in an e-discovery system is provided. A list of first-order documents and document custodians within a base state of the e-discovery system are identified based on a plurality of terms corresponding to a meet and confer practice for a legal matter instance. The plurality of terms is masked within the first-order documents. The first-order documents having the plurality of terms masked are divided into groups. A list of second-order documents is generated from a group of documents. A list of second-order document custodians is generated based on corresponding custodian relationships to second-order documents. Finally, each second-order document custodian in the list of second-order document custodians that has a corresponding rank exceeding a defined rank threshold level is identified as an official document custodian in the e-discovery system.

Abstract: Described herein are technologies that facilitate effective use (e.g., indexing and searching) of non-text machine data (e.g., audio/visual data) in an event-based machine-data intake and query system.

Abstract: An information processing apparatus according to the application concerned includes an obtaining unit and a generating unit. The obtaining unit obtains a first-type graph including a plurality of node corresponding to a plurality of search target. The generating unit generates, based on placement of the plurality of nodes in the first-type graph, a second-type graph that includes a virtual node representing a node not associated to a search target by adding the virtual node to the first-type graph.

Abstract: A data security method, including creating an interaction graph, by analyzing collected interaction events between users and between users and files and/or records, where a respective node of the interaction graph represents a specific one of a user, a record, and a file, where a respective edge indicates an interaction between respective users or between a respective user and a respective file and/or record, where an interaction weight assigned to the respective edge indicates an amount of the interaction, monitoring an attempt by a target user to access a target file and/or record, computing a target interaction weight between the target user and the target file and/or record from the interaction graph, and in response to the target interaction weight being below a target threshold, at least one of filtering security alerts, and blocking access by the target user to the target file and/or record.

Abstract: Introduced here are approaches to determining causal relationships in mixed datasets containing data related to continuous variables and discrete variables. To accomplish this, a marketing insight and intelligence platform may employ a multi-phase approach in which dependency is established before the data related to continuous variables is discretized. Such an approach ensures that information regarding dependence is not lost through discretization.

Abstract: Provided herein are systems and methods for a database object (e.g., materialized table) configuration including scheduling refreshes of the materialized table. For example, a method includes determining a dependency graph for a first MT. The dependency graph comprises a second MT from which the first MT depends. The first MT includes a query on one or more base tables and a lag duration value. The lag duration value indicates a maximum time period that a result of a prior refresh of the query can lag behind a current time instance. A tick period is selected for a set of ticks based on the lag duration value. The set of ticks corresponds to a set of aligned time instances. Refresh operations are scheduled for the first and second MTs at corresponding time instances from the set of aligned time instances. The corresponding time instances are separated by the tick period.